Sledovat
Jason Lines
Jason Lines
Associate Professor in Computer Science, University of East Anglia
E-mailová adresa ověřena na: uea.ac.uk - Domovská stránka
Název
Citace
Citace
Rok
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A Bagnall, J Lines, A Bostrom, J Large, E Keogh
Data mining and knowledge discovery 31, 606-660, 2017
19022017
Classification of time series by shapelet transformation
J Hills, J Lines, E Baranauskas, J Mapp, A Bagnall
Data mining and knowledge discovery 28, 851-881, 2014
6832014
Time series classification with ensembles of elastic distance measures
J Lines, A Bagnall
Data Mining and Knowledge Discovery 29, 565-592, 2015
6612015
Time-series classification with COTE: the collective of transformation-based ensembles
A Bagnall, J Lines, J Hills, A Bostrom
IEEE Transactions on Knowledge and Data Engineering 27 (9), 2522-2535, 2015
6162015
The UEA multivariate time series classification archive, 2018
A Bagnall, HA Dau, J Lines, M Flynn, J Large, A Bostrom, P Southam, ...
arXiv preprint arXiv:1811.00075, 2018
5592018
A shapelet transform for time series classification
J Lines, LM Davis, J Hills, A Bagnall
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
5042012
Time series classification with HIVE-COTE: The hierarchical vote collective of transformation-based ensembles
J Lines, S Taylor, A Bagnall
ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (5), 1-35, 2018
4352018
sktime: A unified interface for machine learning with time series
M Löning, A Bagnall, S Ganesh, V Kazakov, J Lines, FJ Király
arXiv preprint arXiv:1909.07872, 2019
3312019
HIVE-COTE 2.0: a new meta ensemble for time series classification
M Middlehurst, J Large, M Flynn, J Lines, A Bostrom, A Bagnall
Machine Learning 110 (11), 3211-3243, 2021
2922021
Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification
J Lines, S Taylor, A Bagnall
2016 IEEE 16th international conference on data mining (ICDM), 1041-1046, 2016
2612016
Transformation based ensembles for time series classification
A Bagnall, L Davis, J Hills, J Lines
Proceedings of the 2012 SIAM international conference on data mining, 307-318, 2012
1722012
The UEA & UCR time series classification repository
A Bagnall, J Lines, W Vickers, E Keogh
URL http://www. timeseriesclassification. com 122, 2018
1482018
A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates
J Large, J Lines, A Bagnall
Data mining and knowledge discovery 33 (6), 1674-1709, 2019
882019
Classification of household devices by electricity usage profiles
J Lines, A Bagnall, P Caiger-Smith, S Anderson
Intelligent Data Engineering and Automated Learning-IDEAL 2011: 12th …, 2011
852011
An experimental evaluation of nearest neighbour time series classification
A Bagnall, J Lines
arXiv preprint arXiv:1406.4757, 2014
752014
On the usage and performance of the hierarchical vote collective of transformation-based ensembles version 1.0 (hive-cote v1. 0)
A Bagnall, M Flynn, J Large, J Lines, M Middlehurst
Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop …, 2020
672020
Alternative quality measures for time series shapelets
J Lines, A Bagnall
Intelligent Data Engineering and Automated Learning-IDEAL 2012: 13th …, 2012
542012
Is rotation forest the best classifier for problems with continuous features?
A Bagnall, M Flynn, J Large, J Line, A Bostrom, G Cawley
arXiv preprint arXiv:1809.06705, 2018
492018
A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1. 0
A Bagnall, M Flynn, J Large, J Lines, M Middlehurst
arXiv preprint arXiv:2004.06069, 2020
292020
Ensembles of elastic distance measures for time series classification
J Lines, A Bagnall
Proceedings of the 2014 SIAM International Conference on Data Mining, 524-532, 2014
282014
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Články 1–20